Age of Synchronization Minimization Algorithms in Wireless Networks with Random Updates under Throughput Constraints

Area of Science:

• Wireless communication networks
• Information theory
• Optimization theory

Background:

• Wireless networks face challenges with data freshness due to random updates and shared channels.
• The age of synchronization (AoS) is a key metric for data freshness, measuring time since the last update.
• Efficiently managing status updates is crucial for maintaining data timeliness in dynamic network environments.

Purpose of the Study:

• To minimize the weighted sum of average age of synchronization (AoS) across a wireless network.
• To ensure minimum throughput requirements for each node are met.
• To develop and analyze scheduling policies for both central and distributed wireless network scenarios.

Main Methods:

• Developed optimal stationary randomized and max-weight policies for central scheduling with and without transmission feedback.
• Proposed a novel distributed scheduling policy for decentralized network management.
• Analyzed scheduling policies for low computational complexity.

Main Results:

• Proposed policies successfully satisfy throughput constraints in central scheduling scenarios.
• The max-weight policy demonstrated AoS performance close to the theoretical lower bound.
• Numerical simulations validated the effectiveness of the developed scheduling strategies.

Conclusions:

• The proposed low-complexity scheduling policies effectively balance data freshness and throughput in wireless networks.
• The developed methods offer practical solutions for optimizing status update timeliness.
• Further research can explore adaptive strategies for more dynamic network conditions.